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Found 7,035 Skills
Guides application developers in designing correct and performant transaction patterns for CockroachDB, covering transaction lifetime, implicit vs explicit transactions, retry handling with exponential backoff, pushing invariants into SQL, selective pessimistic locking, set-based operations, connection pooling, prepared statements, keyset pagination, follower reads, and separating business logic from database logic. Use when building applications on CockroachDB, designing transaction workflows, handling retries, optimizing application-layer database interactions, or configuring connection pools.
Use when working with AdonisJS Lucid ORM and SQL layer: database configuration, migrations, schema generation, schema classes, models, CRUD operations, model query builder, query scopes, hooks, serialization, relationships, transactions, pagination, debugging, validation rules, model factories, seeders, or database query builders. Trigger for tasks involving @adonisjs/lucid, database/schema.ts, app/models, database/migrations, database/factories, database/seeders, db service queries, Lucid relationships, or model behavior.
Map environmental/industrial chemicals to mechanistic adverse outcome pathways (AOPs) using AOPWiki, quantify toxicological hazard (PubChemTox GHS/carcinogen classification, LD50 values), and link chemical stressors to gene targets and disease endpoints via CTD for regulatory risk assessment. Use when asked about AOP stressor mapping, GHS hazard categories, LD50 data, IARC carcinogen classification, or mechanism-based risk assessment for non-drug chemicals.
Scans the codebase to generate project-doc.md and AGENTS.md. Runs a full scan on first use and a smart delta scan on subsequent runs. Uses understand-anything + context-mode when available, falls back to native tools otherwise. Only updates AGENTS.md on detected architectural changes with human confirmation.
Configure AI agents via the imperative SDK / REST API — for no-code dashboard setups, webhook-based tools, and knowledge bases.
Guides technical support engineering—customer ticket investigation, reproduction, log and API analysis, root-cause isolation, workaround communication, engineering escalation with evidence, and knowledge-base fixes for product bugs and integration issues. Use when debugging a customer-reported issue, writing a repro for engineering, analyzing API errors, drafting technical replies, or improving support runbooks—not for CS program design, renewals, or billing ops (customer-ops-specialist), production incident command (incident-management-engineer), building product features (fullstack-software-engineer), or company-wide crisis statements and launch announcements (communication-lead), or exec/VIP and community escalation program design (community-executive-escalations-program-manager). Product how-to, macros, and ticket triage without deep debugging: product-support-specialist.
Generate a fully working React + Vite app that explains a codebase's workflows, data types, and architecture through interactive visuals — click-to-step animated walkthroughs with auto-play, sequence diagrams, animated packet tracers, message inspectors that toggle between named-field view and raw JSON, and collapsible code peeks with file:line citations. Splits the repo into 4–6 domain clusters and dispatches one content agent per cluster to write the pages in parallel. The skill bundles its own reference pages (under references/examples/) so it works in any repo. Use this skill whenever the user asks for interactive docs, animated explainers, an "agent team" for docs, one page per domain, wants to visualize a system's request flow or wire protocol, or any visual documentation site. Requires CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 in .claude/settings.json.
Manage cloud infrastructure — monitor deployments, scale resources, manage databases, and handle domain operations across all supported providers.
Create and manage MotherDuck data shares for zero-copy data distribution. Use when sharing databases with team members, other organizations, or making data publicly available.
Mandatory analysis workflow for understanding codebase before changes
Applicable when you need to resolve ongoing git merge/rebase conflicts.
Synthesizes trust boundaries, attack surfaces, and attacker profiles into a living threat model. Use as Stage B of the Knowledge Base generation process, reading architecture and entity definitions from the KB. Don't use for analyzing source code or extracting raw learnings from JSONL files.